Learning Shortcuts — A Response

I have a confession to make: I don’t like shortcuts. Of course, I may be deluding myself as I eschew quill and parchment for a fancy laptop as I write this. But shortcuts, to me, feel like placing destination before journey, and efficiency before purpose. Yet dismissing the article “Learning Shortcuts” on the basis of a personal quirk would be deeply disingenuous. And terminology aside, I must confess that I’ve found myself grappling with exactly the same questions the article raises as I’ve wrestled with what AI is capable of, and where the potential pitfalls might lie. 

Amongst other things, I’m an author, and I guard my craft as a writer jealously. My ability to use words and narrative is as much a part of who I am as it is what I do. And yet, as someone who studies the art and science of navigating advanced technology transitions, I experiment with and use artificial intelligence extensively. I have long conversations with it. I code with it. I write papers on it. I have days where it feels like a jet pack for the mind, and others where I wish I’d never heard of it. And I write with it. A lot. 

Through all of this, I’m constantly asking how it’s benefiting me and others, how it might be harming me and what I do, and what I’m not asking that I probably should be. And to be honest, the more I dig, the less certain I am that I have the answers. Yet AI is now so ubiquitous that, just as a fish caught in a flood doesn’t have the luxury of opting out of the torrent, I don’t think we have the luxury of being bystanders as AI transforms our world.

So how do we respond? One approach is to ask exactly the questions posed in “Learning Shortcuts:” which “shortcuts” (or “affordances” if you want to be quill-and-parchment fancy) are good, which are bad, and which reveal something important about the future of learning?

Here, from my own work and practice, there’s a lot that lands in the “good” ledger. For someone who’s already good at what they do, AI can, in my experience, be a powerful accelerator. And this extends to learning. But it’s an accelerator that needs its own unique set of skills to wield effectively. 

One of these skills, I believe, is discernment. Speed is all well and good, but it’s not that helpful if you end up in the wrong place. And AI without discernment can easily devolve into all speed and no direction. Another is care — not necessarily the touchy-feely kind (although that’s good as well), but a disciplined practice that affects what you do and why, together with the impacts it has on yourself and others. 

Care as a practice is, in my experience, deeply connected with how AI is used, not whether it’s used (although as in all things, there are exceptions). In some cases, using AI as a shortcut might be seen as “care-less” if it diminishes value to someone else (or even yourself), but “care-full” if it increases your ability to produce something of benefit to others. For instance, a 1000-word AI-generated article that takes more time to read than it took to create might be considered to be “care-less.” On the other hand, a 2000-word AI-assisted piece that has been deeply researched, sweated over, and meticulously edited is something I would consider to be “care-full” as it demonstrates care and respect for the reader.¹

This is where intent and process are, I believe, critical, and why I’m leery of criticizing AI use without understanding what lies behind it. And used with care and discernment, AI is, without a doubt, a powerful learning accelerator.

But like all powerful technologies, it also has its dark side — especially as even the creators of the latest models don’t understand what they are capable of. Yet it’s becoming increasingly easy to slip into “Sorcerer’s Apprentice” mode and treat AI like a magic broom. This isn’t helped by the oft-made assumption that it’s simply another efficiency tool. But there’s a growing body of research that suggests that treating AI as just a tool overlooks how it may be impacting how we think, what we believe, and even how we behave.  

A few months ago, I was grappling with just this — I was on a bit of a Fantasia kick at the time. As I wrote on my Substack, “[i]n the Sorcerer’s Apprentice scene, Mickey risks being swept away by the consequences of his naivety. But in a world where transformative AI touches everything we do, ignoring its power may be just as naive as wielding it without understanding.”

Mickey's biggest mistake, I argued, wasn't that he embraced sorcery he didn't understand, but that he acted with certainty unshaken by his ignorance. And I ended up wondering whether the modern equivalent is acting with certainty in the unquestioned benefits of AI, or even in trusting that traditional mastery alone is enough.²

And this, perhaps, is the biggest takeaway to me as we think about AI and learning shortcuts. Not whether “shortcuts” is the right word, or how fast we can go with AI, or even what mastery looks like. But how we avoid certainty unshaken by ignorance as we lean into learn how to use AI for good.

Andrew Maynard studies and writes about how to successfully navigate advanced technology transitions — including AI. He is a professor in ASU’s Thunderbird School of Global Management

¹In the book AI and the Art of Being Human, care is one of the four postures that my co-author Jeffrey Abbot and I explore, along with clarity, curiosity, and discernment.

²Ten Questions about AI and Higher Education. https://www.futureofbeinghuman.com/p/ten-questions-about-ai-and-higher